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Found 4 papers, 2 papers with code
TeleMoMa: A Modular and Versatile Teleoperation System for Mobile Manipulation
This problem is more severe in mobile manipulation, where collecting demonstrations is harder than in stationary manipulation due to the lack of available and easy-to-use teleoperation interfaces.
Mini-BEHAVIOR: A Procedurally Generated Benchmark for Long-horizon Decision-Making in Embodied AI
We present Mini-BEHAVIOR, a novel benchmark for embodied AI that challenges agents to use reasoning and decision-making skills to solve complex activities that resemble everyday human challenges.
Causal Policy Gradient for Whole-Body Mobile Manipulation
Current approaches often segregate tasks into navigation without manipulation and stationary manipulation without locomotion by manually matching parts of the action space to MoMa sub-objectives (e. g. learning base actions for locomotion objectives and learning arm actions for manipulation).
GLSO: Grammar-guided Latent Space Optimization for Sample-efficient Robot Design Automation
In this work, we present Grammar-guided Latent Space Optimization (GLSO), a framework that transforms design automation into a low-dimensional continuous optimization problem by training a graph variational autoencoder (VAE) to learn a mapping between the graph-structured design space and a continuous latent space.
